A virtual microscope slide typically comprises digital data representing a magnified image of a microscope slide. Because the virtual slide is in digital form, it can be stored on a 10 medium, such as in a computer memory, for example, and can be transmitted over a communication network, such as the Internet, an intranet, etc., to a viewer at a remote location.
Virtual slides offer advantages over traditional microscope slides. In some cases, a virtual slide can enable a physician to render a diagnosis more quickly, conveniently and economically than is possible using traditional microscope slides. For example, a virtual slide 15 may be made available to a remote user, such as a specialist in a remote location, for example, over a communication link, enabling the physician to consult with the specialist and provide a diagnosis without delay. Alternatively, the virtual slide can be stored in digital form indefinitely, for later viewing at the convenience of the physician or specialist.
Typically, a virtual slide is generated by positioning a microscope slide (which 20 contains a sample for which a magnified image is desired) under a microscope objective lens, capturing one or more images covering all, or a portion, of the slide, and then combining the images to create a single, integrated, digital image of the slide. It is often desirable to divide a slide into multiple regions and generate a separate image for each region. This is because, in many cases, an entire slide is often larger than the field of view of a high-power objective lens (a 10×, 20×, or even 40×, for example) and multiple images must be obtained in order to render the entire slide image at the desired magnification. Additionally, the surfaces of many tissue types are uneven and contain local variations that make it difficult to capture an in-focus image.
When the sample is larger than a single field of view, the regions that are imaged must be combined in some fashion in order to produce a single image. These blocks of images must be combined such that image produced is without artifact due to image misalignment. This can be accomplished in several ways. One system might utilize a very accurate x-y stage in order to produce images at precise positions such that, in the claimed theory, simple abutting of the images should produce a seamless, well registered set of images. Other methods rely on software algorithms to determine the optimal registration for a set of images. This process is often referred to, in the art, as stitching (or alternatively, mosaicing). These stitching algorithms take a number of images and attempt to optimally position these blocks of images such that a seamless well formed image results.
Some algorithms will utilize image modification, such as image warping, to produce more optimal alignment between blocks of images. This process has many drawbacks, particularly in the case of medical imaging systems, since accuracy is so important to a diagnostician. Image modification may be undesirable, as it can lead to side effects such as resolution reduction and aliasing. Also, image modification can be very computationally expensive and time consuming. Furthermore, creation of an optimal image position within a global coordinate system may result multiple solutions. Which solution to select and the reproducibility of the process are issues that need to be addressed.